Maxim Raginsky: Universal Approximation of Sequence-to-Sequence Transformations
Maxim Raginsky: Universal Approximation of Sequence-to-Sequence Transformations
|
Yükleniyor...
Lütfen bekleyiniz...
Type
Size

 İlgili Videolar

Maxim Raginsky: Universal Approximation of Sequence-to-Sequence Transformations

Maxim Raginsky: Universal Approximation of Sequence-to-Sequence Transformations

|
PR-250: Are Transformers universal approximators of sequence-to-sequence functions?

PR-250: Are Transformers universal approximators of sequence-to-sequence functions?

|
NASIT 2019 Tutorial - Maxim Raginsky - Information, Concentration, and Learning

NASIT 2019 Tutorial - Maxim Raginsky - Information, Concentration, and Learning

|
Maxim Raginsky: "A mean-field theory of lazy training in two-layer neural nets"

Maxim Raginsky: "A mean-field theory of lazy training in two-layer neural nets"

|
Higher order approximation for sequences converging in the mod-Gaussian sense

Higher order approximation for sequences converging in the mod-Gaussian sense

|
Maxim Raginsky: The limits of control: An information-theoretic viewpoint

Maxim Raginsky: The limits of control: An information-theoretic viewpoint

|
Max Raginsky on Foundation of Data Science Series (Oct 21, 2021)

Max Raginsky on Foundation of Data Science Series (Oct 21, 2021)

|
Neural SDEs: Deep Generative Models in the Diffusion Limit - Maxim Raginsky

Neural SDEs: Deep Generative Models in the Diffusion Limit - Maxim Raginsky

|
Information-Theoretic Lower Bounds for Distributed Function Computation

Information-Theoretic Lower Bounds for Distributed Function Computation

|
A Mean-Field Theory of Lazy Training in Two-Layer Neural Nets: ...

A Mean-Field Theory of Lazy Training in Two-Layer Neural Nets: ...

|
1st School in Machine Learning of Dynamic Processes and Time Series Analysis - part 2

1st School in Machine Learning of Dynamic Processes and Time Series Analysis - part 2

|
Yuliy Baryshnikov (1/19/20): Linear Obstacles in Linear Systems and Ways to Avoid Them

Yuliy Baryshnikov (1/19/20): Linear Obstacles in Linear Systems and Ways to Avoid Them

|
First IBM Research Workshop on the Informational Lens: Day 4. Talk by Yuliy Baryshnikov

First IBM Research Workshop on the Informational Lens: Day 4. Talk by Yuliy Baryshnikov

|
"In Soviet Russia Machine Learns You" by Max Raginsky

"In Soviet Russia Machine Learns You" by Max Raginsky

|
From individual-level cognition to collective dynamics - Ralf Kurvers

From individual-level cognition to collective dynamics - Ralf Kurvers

|
Alec Smith at the Arizona Think Tank for Behavioral Decision Making

Alec Smith at the Arizona Think Tank for Behavioral Decision Making

|
[깊게 배우는 머신러닝] 1.1 머신러닝은 곧 통계적 학습(Statistical Learning)이다!

[깊게 배우는 머신러닝] 1.1 머신러닝은 곧 통계적 학습(Statistical Learning)이다!

|
Copyright. All rights reserved © 2025
Rosebank, Johannesburg, South Africa